Кафедра Інформаційно-вимірювальних технологій (ІВТ)
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Перегляд Кафедра Інформаційно-вимірювальних технологій (ІВТ) за автором "Lutskyy, S."
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Публікація System-information approach to uncertainty of process and system parameters(ХНУРЕ, 2021) Lutskyy, S.The subject matter of research in the article is a system-information approach to the uncertainty of the parameters of processes and systems of the technosphere as one of the scientific directions of using information theory in metrology and other scientific areas. The system-information approach is based on the definition of the term "information" of the properties of the system, its content and meaning. The solution of the basic problem in metrology, obtaining "information" of the quantitative characteristics of the true value of the properties of objects and phenomena that reveal the regularities of the environment, is a complex scientific problem. The instrument for obtaining information about the properties of the system is the measurement process. One of the directions in the development of measurement theory is the concept of uncertainty. The goal of the work is to research of non-traditional solutions to problems of technical-cybernetic systems based on the system-information approach to the uncertainty of the parameters of processes and systems. The article solves the following tasks: to analyze the assessment of the parameters of technological processes and systems based on the system-information approach; to develop system-information methods and algorithms for the effective use of discrete-probabilistic information in technical-cybernetic systems; to develop principles and approaches for using the system information assessment of the uncertainty of the Planck units, use of system-information modeling in various scientific directions. The following methods are used: system-information approach to processes and systems, methodology of system-information modeling of the measured value; system information methodology for the assessment of the measured quantity and uncertainty. The following results were obtained: developed a system-information methodology for assessing the nominal parameter has been developed, which provides indirect control over the independent parameters associated with it; systemic and information methods for the effective use of discrete-probabilistic information in technical and cybernetic systems have been developed; a system-information methodology for calculating the energy equivalent of product performance indicators has been developed; the principle of calculating the efficiency of manufacturing a product based on the energy equivalent of Planck units is formulated. Conclusions: The solution of the set tasks on the basis of the system-information approach to the uncertainty of the parameters of processes and systems makes it possible, from the system-information point of view, to study the regularities of the stages of the life cycle of technical-cybernetic systems and conservation laws.Публікація System-information models for intelligent information processing(ХНУРЕ, 2022) Korablyov, M.; Lutskyy, S.The subject of the study is system-information models of processes and systems and their use for intelligent processing of information in production tasks. The use of intelligent information processing in production management systems is currently one of the key areas of development of informatics. The aim of the work is to develop system-information models of processes and systems for intelligent information processing allowing to analyze and solve production problems, in conditions of uncertainty. In the article the following tasks are solved: to analyze approaches to the definition of information characteristics of processes and systems; to develop the basis for modeling of system-information processes and systems for intelligent information processing; to develop system-information models and ways of their application for intelligent information processing in the tasks of production. The following methods are used: system-information approach to processes and systems; system-information modeling of processes and systems. The following results were obtained: the analysis of approaches to the definition of information characteristics of processes and systems; developed principles of modeling system-information processes and systems for intelligent processing of information; introduced the concepts of system information and information measure; developed system-information models and methods of their application for the intelligent processing of information in the tasks of production. Conclusions. The development of methods for solving various classes of practical problems using intelligent information processing is one of the key areas of research in computer science. The developed system-information models of processes and systems for intelligent information processing allow analyzing and solving problems. Thereby increase the efficiency of solving problems of analysis, synthesis and forecasting of production systems and technologies, as well as problems of production management. The system-information approach to processes and systems operates with new concepts – system information and information measure, it allowed developing system-information models for intelligent processing of information, as well as ways of their application at stages of product life cycle, which allowed solving problems of production. System-information models of processes and systems describe interaction between source and receiver on information level on the basis of sensitivity threshold. The communication channel between the source and the receiver of information operates, as a rule, under conditions of uncertainty, which can lead to the loss of information during transmission due to possible changes in the characteristics of the system. To describe their interaction, some models of intelligent information processing can be used, in particular, neural network models or fuzzy inference models. Their use will improve the efficiency of receiver state prediction, taking into account the state of the transmitter and the conditions of communication channel operation. The presented article has shown the relevance of developing system-information models for intelligent information processing at the levels of data reception, interpretation and ommunication, which allows expanding the class of solved production tasks.